Role Summary
Designs, develops, deploys, and optimises Artificial Intelligence (AI) and Machine Learning (ML) solutions within the Software Engineering Centre of Excellence (CoE). Works closely with software engineering squads, data teams, architects, DevOps, and business stakeholders to build scalable AI-enabled products, intelligent automation capabilities, predictive models, and advanced analytics solutions that support business and customer outcomes.
Responsibilities
Design, develop, train, test, and deploy machine learning and AI models for enterprise and customer-facing solutions
Collaborate with software engineering squads, data engineers, architects, and product owners to integrate AI capabilities into digital products and platforms
Build scalable AI/ML pipelines and support operationalisation of models within production environments
Develop and optimise models for predictive analytics, automation, recommendation engines, NLP, GenAI, and intelligent decisioning solutions
Work with large structured and unstructured datasets to support AI solution development
Support AI platform engineering, model governance, monitoring, and continuous improvement practices
Implement MLOps and DevOps best practices for model deployment, testing, monitoring, and lifecycle management
Evaluate and recommend AI frameworks, tools, accelerators, and emerging technologies
Support development of reusable AI engineering assets, accelerators, and standards within the CoE
Collaborate with security, governance, and compliance teams to ensure responsible AI practices and data governance compliance
Support technical solution design, estimation, and implementation planning for AI-enabled initiatives
Provide technical leadership and mentorship to engineering teams on AI/ML engineering practices
Contribute to continuous improvement, innovation initiatives, and AI capability development within the Software Engineering CoE
Qualification & Experience
Bachelor's degree (BA/BS) in Computer Science, Data Science, Artificial Intelligence, Mathematics, Engineering, or related field preferred
At least 8–10 years of experience in software engineering, AI, machine learning, or data engineering environments
At least 5 years of hands-on experience developing and deploying AI/ML solutions in enterprise environments
Experience with machine learning frameworks and tools such as TensorFlow, PyTorch, Scikit-learn, MLflow, LangChain, or similar technologies
Experience with cloud AI platforms and services such as AWS, Azure, or Google Cloud
Experience with MLOps, CI/CD pipelines, containerisation, and cloud-native engineering practices
Strong understanding of software engineering principles, APIs, microservices, and scalable system design
Experience working within Agile software delivery teams
Preferred Skills
AI and machine learning model development
Generative AI and Large Language Model (LLM) integration
Natural Language Processing(NLP)
Predictive analytics and data modelling
MLOps and AI operationalisation
Python, SQL, and modern programming frameworks
Cloud engineering and distributed systems
API and microservices integration
Analytical and problem-solving capability
Strong stakeholder engagement and communication skills
Ability to simplify technical concepts for business stakeholders
Process improvement and innovation mindset
Ability to work independently and across multiple agile squads
Good communication (written and oral) and interpersonal skills
Good organisational, multi-tasking, and time-management skills
Originally posted on Himalayas